This is a Moose project bootstrapped with moose init

Demo Application

Getting Started

Prerequisites

• Docker Desktop
• Node

1. Install Moose: bash -i <(curl -fsSL https://fiveonefour.com/install.sh) moose
2. Install dependencies: cd aircraft/moose && npm install
3. Run Moose: moose dev
4. In a new terminal, install frontend dependencies cd aircraft/frontend && npm install
5. Configure the frontend API URL (optional):
   • Copy the example environment file: cp .env.example .env.local
   • Edit .env.local and set
     • NEXT_PUBLIC_API_URL to your backend URL
       • For local development, the default is http://localhost:4000
       • For production deployments, update to your Boreal URL (e.g., https://514-demos-planes-main-59be4.boreal.cloud)
     • NEXT_PUBLIC_MCP_SERVER_URL to your MCP URL
       • For local development, the default is http://localhost:4000
       • For production deployments, update to your Boreal URL (e.g., https://514-demos-planes-main-59be4.boreal.cloud)
     • ANTHROPIC_API_KEY to your private Anthropic API key
6. Run frontend: npm run dev

You are ready to go!

You can start editing the app by modifying primitives in the app subdirectory. The dev server auto-updates as you edit the file.

This project gets data from http://adsb.lol.

Chat Feature

This project includes an AI-powered chat interface that allows you to query aircraft tracking data using natural language.

Usage

1. Start the backend (moose) and frontend servers (see Getting Started above)
2. Open the dashboard at http://localhost:3000
3. Click the floating chat button in the bottom-right corner
4. Ask questions about your aircraft data in natural language

Example Questions

• "How many aircraft are being tracked?"
• "Show me the 5 highest flying aircraft"
• "Which aircraft are on autopilot?"
• "What flights are currently on approach?"

Features

• Natural Language Queries: Ask questions in plain English
• SQL Transparency: View the generated SQL queries
• Data Visualization: Results displayed in formatted tables
• Multi-Step Reasoning: See Claude's thought process across multiple iterations

Architecture

The chat feature uses:

• Frontend: NextJS project containing a chat sidebar with Vercel's ai-sdk components
• Backend: Express API w/ MCP server at /tools
• AI Model: Anthropic Claude (claude-haiku-4-5)
• MCP Integration: Model Context Protocol server for ClickHouse queries
• Database: ClickHouse for fast analytics

For more technical details, see:

• Backend documentation: moose/README.md
• Frontend documentation: frontend/README.md

Learn More

To learn more about Moose, take a look at the following resources:

• Moose Documentation - learn about Moose.

Deploy on Boreal

The easiest way to deploy your Moose app is to use the Boreal from Fiveonefour, the creators of Moose.

Sign up.

License

This template is MIT licenced.